We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate the problem of optimally choosing the mobile devices that will serve as gateways from the cellular to the ad hoc network, the ad hoc routes from the gateways to individual devices, and the layers to deliver on these ad hoc routes.

We develop a Mixed Integer Linear Program (MILP)-based algorithm, called POPT, to solve this optimization problem. Pocket delivers the highest possible video quality and optimization problem that determines:

1) The mobile devices that will serve as gateways and relay video data from the cellular network to the ad hoc network,

2) The multihop ad hoc routes for disseminating video data

3) The subsets of video data each mobile device relays to the next hops under capacity constraints. We formulate the optimization problem into a Mixed Integer Linear Program (MILP), and propose an MILP-based algorithm, called POPT, to optimally solve the problem.

We recommend the THS algorithm for video streaming over hybrid cellular and ad hoc networks. Last, we also build a real video dissemination system among multiple Android smart phones over a live cellular network. Via actual experiments, we demonstrate the practicality and efficiency of the proposed THS algorithm.

We call it Tree-Based Heuristic Scheduling (THS) algorithm, and it works as follows: We first sort all the transmission units in the W-segment scheduling window in descending order of importance, by layer, segment, and video. We then go through these WL units, and sequentially schedule the transmissions to all mobile devices.

1.2 INTRODUCTION

Mobile devices, such as smart phones and tablets, are getting increasingly popular, and continue to generate record-high amount of mobile data traffic. For example, a Cisco report indicates that mobile data traffic will increase 39 times by 2015. Sixty six percent of the increase is due to video traffic. Unfortunately, existing cellular networks were designed for unicast voice services, and do not natively support multicast and broadcast. Therefore, cellular networks are not suitable for large-scale video dissemination. This was validated by a measurement study, which shows that each HSDPA cell can only support up to six mobile video users at 256 kbps. Thus, disseminating videos to many mobile users over cellular networks could lead to network congestion and degraded user experience.

This network capacity issue may be partially addressed by deploying more cellular base stations, installing dedicated broadcast networks (such as Digital Video Broadcast- Handheld, DVB-H), or upgrading the cellular base stations to support Multimedia Broadcast Multicast Service (MBMS). However, these approaches all result in additional costs for new network infrastructure, and might not be fully compatible with existing mobile devices. Hence, a better way to disseminate videos to many mobile users is critical to the profitability of cellular service providers.

We study video dissemination in hybrid cellular and ad hoc networks in the underlying network, consisting of one or several base stations and multiple mobile devices equipped with heterogeneous network interfaces. Mobile devices not only connect to the base station over the cellular network, but also form an ad hoc network using short-range wireless protocols such as WiFi and Bluetooth. Mobile devices relay video traffic among each other using ad hoc links, leveraging such a free spectrum to alleviate bandwidth bottlenecks and cut down the expense of cellular service providers. Throughout the paper, we denote mobile devices that directly receive video data over the cellular network and relay the receiving data to other mobile devices over the ad hoc network as gateways.

1.3 SCOPE OF THE PROJECT

3G, and 4G cellular networks, and examples of ad hoc networks are WiFi ad hoc and Bluetooth networks. Mobile devices can always receive video data from the base station via cellular links. Distributing videos in a hybrid network is challenging because: Wireless networks are dynamic in terms of connectivity, latency, and capacity and video data require high throughput and low latency. To cope with these challenges, we employ layered video coding, such as H.264/MPEG4.

1.4 LITRATURE SURVEY

RATE CONTROL AND STREAM ADAPTATION FOR SCALABLE VIDEO STREAMING OVER MULTIPLE ACCESS NETWORKS

Author: C. Hsu, N. Freris, J. Singh, and X. Zhu

Publish:” Proc. Int’l Packet Video Workshop (PV ’10), pp. 1-8, Dec.2010.

In a multihomed video streaming system, a video sequence is simultaneously transmitted over multiple access networks to a client. In this paper, we formulate the rate control and a stream adaptation problem into a unified optimization problem, which determines the sending rates of individual networks, selects which video packets to transmit, and assigns each packet to an access network. We propose two heuristic algorithms with a trade-off between optimality and computational complexity. One of the proposed algorithms runs faster, while the other one results in better video quality. We propose a hybrid algorithm that demonstrates a good balance between optimality and computational complexity. We conduct extensive packet-level simulations to evaluate our algorithms using real network conditions and actual scalable video streams. We compare our algorithms against the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) standard. The simulation results show that our algorithms significantly outperform current systems while being TCP-friendly. Our algorithms achieve at least 10 dB quality improvements over DCCP and result in up to 83% packet delivery delay reduction.

CHAPTER 2

2.0 SYSTEM ANALYSIS

2.1 EXISTING SYSTEM:

Linear Program (LP)-based algorithm called MTS, for lower time complexity generic ad hoc protocols do not work well in hybrid cellular and WiFi ad hoc networks, and may lead to:

1) degraded overall throughput, 2) unfair resource allocation, and 3) low resilience to mobility. They propose two approaches to improve the efficiency of ad hoc protocols. First, the base station can run optimization algorithms for the WiFi ad hoc network, for example, to build optimized routes. Second, mobile devices connected to other access networks can offload traffic from the cellular network to those access networks, so as to avoid network congestion around the base station.

2.1.1 DISADVANTAGES:

Existing algorithms achieve at least 10 dB quality improvements and result in up to 80% packet delivery delay reduction.

2.2 PROPOSED SYSTEM:

We propose a hybrid network, in which each multicast group is either in the cellular in the ad hoc mode. Initially, all multicast groups are in ad hoc mode, and when the bandwidth requirement of a group exceeds the ad hoc network capacity, the base station picks up that group and switches it into the cellular mode.

In the ad hoc network, a flooding routing protocol is used to discover neighbors and a heuristic is employed to forward video data. Our work differs from in several aspects: 1) we propose a unified optimization problem that jointly finds the optimal gateway mobile devices, ad hoc routes, and video adaptation, 2) we consider existing cellular base stations that may not natively support multicast, and 3) we employ Variable-Bit-Rate (VBR) streams.

More specifically, we empirically measure the mapping between the node location and link capacity several times, and use the resulting values for capacity estimation. We adopt the video traces of H.264/MPEG4 layered videos from an online video library. The mean bit rate and average video quality for each layer of the considered videos are given in Table 2. In this paper, we report sample simulation results of distributing Crew. However, the proposed formulation and solutions are general and also work for the scenarios where mobile devices watch different videos.

2.2.1 ADVANTAGES:

1. The links into mobile devices on breadth-first trees of transmission units with higher quality improvement values are given higher priorities.

2. The links with higher ad hoc link capacities are given higher priorities.

3. The links from mobile devices with higher cellular link capacities are given higher priorities.

2.3 HARDWARE & SOFTWARE REQUIREMENTS:

2.3.1 HARDWARE REQUIREMENT:

v Processor – Pentium –IV

Speed – 1.1 GHz
- RAM – 256 MB (min)
- Hard Disk – 20 GB
- Floppy Drive – 1.44 MB
- Key Board – Standard Windows Keyboard
- Mouse – Two or Three Button Mouse
- Monitor – SVGA

2.3.2 SOFTWARE REQUIREMENTS:

Operating System : Windows XP
Front End : JAVA JDK 1.7
Tool : Eclipse
Document : MS-Office 2007

CHAPTER 3

3.0 SYSTEM DESIGN:

Data Flow Diagram / Use Case Diagram / Flow Diagram:

The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system

The data flow diagram (DFD) is one of the most important modeling tools. It is used to model the system components. These components are the system process, the data used by the process, an external entity that interacts with the system and the information flows in the system.

DFD shows how the information moves through the system and how it is modified by a series of transformations. It is a graphical technique that depicts information flow and the transformations that are applied as data moves from input to output.

DFD is also known as bubble chart. A DFD may be used to represent a system at any level of abstraction. DFD may be partitioned into levels that represent increasing information flow and functional detail.

NOTATION:

SOURCE OR DESTINATION OF DATA:

External sources or destinations, which may be people or organizations or other entities

DATA SOURCE:

Here the data referenced by a process is stored and retrieved.

PROCESS:

People, procedures or devices that produce data. The physical component is not identified.

DATA FLOW:

Data moves in a specific direction from an origin to a destination. The data flow is a “packet” of data.

MODELING RULES:

There are several common modeling rules when creating DFDs:

All processes must have at least one data flow in and one data flow out.
All processes should modify the incoming data, producing new forms of outgoing data.
Each data store must be involved with at least one data flow.
Each external entity must be involved with at least one data flow.
A data flow must be attached to at least one process.

3.1 BLOCK DIAGRAM:

ARCHITECTURE DIAGRAM:

3.2 DATAFLOW DIAGRAM:

UML DIAGRAMS:

3.2 USE CASE DIAGRAM:

3.3 CLASS DIAGRAM:

3.4 SEQUENCE DIAGRAM:

3.5 ACTIVITY DIAGRAM:

CHAPTER 4

4.0 IMPLEMENTATION:

UNICAST DATA TRANSFER:

We design a hybrid network that uses a WiFi ad hoc network to route cellular data via other mobile devices with higher cellular data rates. Two neighbor discovery and routing protocols, proactive and on-demand, are proposed. With the former protocol, all devices proactively maintain the states of their immediate neighbors. When a device wants to discover a route to the base station, it issues a route discovery message to a neighbor with the highest cellular data rate. The message is further relayed by the neighbor to its highest rate neighbor until there is no neighbor with higher rate than the relayer or the hop count limit is reached. The final relayer is the one that receives data from the cellular network and propagates data to the original requester. With the on-demand protocol, devices do not maintain their neighbors’ states. A requester discovers a route to the base station by flooding a route discovery message to all its neighbors within a given range.

Higher data rates than that of the previous hops forward the message to the base station, which eventually selects the best path to the requester. Simulation results show that the on-demand protocol typically incurs higher traffic overhead on the cellular network, while the proactive protocol consumes more energy. Through simulations show that generic ad hoc protocols do not work well in hybrid cellular and WiFi ad hoc networks, and may lead to: 1) degraded overall throughput, 2) unfair resource allocation, and 3) low resilience to mobility. They propose two approaches to improve the efficiency of ad hoc protocols. First, the base station can run optimization algorithms for the WiFi ad hoc network, for example, to build optimized routes. Second, mobile devices connected to other access networks can offload traffic from the cellular network to those access networks, so as to avoid network congestion around the base station.

MULTICAST DATA TRANSFER:

Evaluate a hybrid network in which a cellular base station reduces its transmission range to achieve a higher data rate for mobile devices inside its range. Some mobile devices act as gateways and relay data to mobile devices outside the range via a multihop ad hoc network. The analysis and simulation results indicate that up to 70 percent downlink capacity improvement over pure cellular networks is possible. We propose a hybrid network, in which each multicast group is either in the cellular mode or in the ad hoc mode. Initially, all multicast groups are in ad hoc mode, and when the bandwidth requirement of a group exceeds the ad hoc network capacity, the base station picks up that group and switches it into the cellular mode. Park and Kasera consider the gateway node discovery problem, and model the ad hoc interference as a graph coloring problem. Solving this problem allows them to approximate the number of other mobile devices in the transmission range of a specific mobile device in the ad hoc routing problem for multicast services, and also abstract ad hoc interference as a graph. They formulate a problem of finding the relay forest to maximize the overall data rate, and they propose an approximation algorithm.

4.1 ALGORITHM:

A Tree-Based Heuristic Algorithm: THS Both POPT and MTS algorithms employ optimization problem solvers. Although commercial and open-source solvers are available, these solvers might lead to long running time in the worst-case scenarios. Hence, we next propose a greedy scheduling algorithm that does not rely on any solvers. We call it Tree-Based Heuristic Scheduling (THS) algorithm, and it works as follows: We first sort all the transmission units in the W-segment scheduling window in descending order of importance, by layer, segment, and video. We then go through these WL units, and sequentially schedule the transmissions to all mobile devices.

4.2 MODULES:

SERVER CLIENT MODULE:

RESOURCE ALLOCATION:

VIDEO STREAMING:

QUALITY OPTIMIZATION:

4.3 MODULE DESCRIPTION:

SERVER CLIENT MODULE:

Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.

WIMAX RELAY NETWORKS:

WiMAX bandwidth allocation schemes in employ multiple loops to examine the performance of the different combinations of recipients, which results in extremely high computational complexity. The bandwidth allocation scheme proposed in this study applies greedy methods to achieve low computational complexity while incorporating the table-consulting mechanisms to avoid redundant bandwidth allocation scheme can efficiently allocate bandwidth while maintaining low computational complexity. WiMAX provide diverse data rates, H.264/SVC allow a video stream to be split into one base layer and multiple enhancement layers. This study assumes that a video can be split into six layers (one base layer and five enhancement layers) corresponding to the six video quality levels a user with the requirements of 64kbit/s 128 kbit/s can be satisfied by receiving the base layer and one enhancement layer.

RESOURCE ALLOCATION:

Our resource allocation model for two-hop WiMAX relay networks consists of one BS, M RSs, and N SSs. For consistency, the BS is regarded as the 0th RS and is denoted by RS0 in the following discussion, while the RSs are denoted by RS1 to RSM.An SS can associate either with the BS or with one of the RSs, and the number of SSs associated with RSm is denoted by Nm. The notation SSm;n represents the nth SS associated with RSm.

CQm represents the channel quality of the link between the BS and RSm while CQm;n represents the channel quality between RSm and SSm;n. Assume that the video streams for the links with lower channel quality should be transmitted by the modulation schemes with higher reliability.

VIDEO STREAMING:

Scalable video broadcast/multicast solutions efficiently integrates scalable video coding, 3G broadcast and ad-hoc forwarding to balance the system-wide and video quality of all viewers at 3G cell. In our solution, video is downloading into multiple layers. The base station broadcasts different layers at different rates to cover viewers at different ranges. All viewers are guaranteed to receive the base layer, and viewers closer to the base station can receive more enhancement layers. Using WiMAX Relay Networks connections, viewers far away from the base station can obtain from their neighbors closer to the base station the enhancement layers that they cannot receive directly from the base station. Our solution strikes a good balance between the average and worst-case performance for all viewers in the cell. We design multi-hop relay routing schemes to exploit the broadcast nature of ad-hoc transmissions and eliminate redundant video relays from helpers to their receivers.

QUALITY OPTIMIZATION:

Our channel qualities of these links, BSs and RSs can dynamically adapt the downlink modulation and coding schemes (MCSs) for data transmission. When RSs are deployed at appropriate locations between the BSs and SSs, the end-to-end channel qualities can be improved and the BSs and RSs can adopt high data-rate MCSs. Based on this improvement in data rate, IEEE 802.16j systems can offer higher throughput and serve more users than IEEE 802.16e systems. Based on the performance enhancements above, IEEE 802.16j has the potential to provide real-time video multicast services such as mobile IPTV, live video streaming (e.g., athletic events), and online gaming).

However, the BSs should allocate bandwidth efficiently to support such bandwidth-hungry services while guaranteeing the quality of user experience (QoE). The bandwidth allocation problems in IEEE 802.16j networks are more challenging than those in IEEE 802.16e networks because the BSs allocate bandwidth not only to the SSs, but also to the RSs. Multicasting also complicates the bandwidth allocation problems of these factors, designing an efficient bandwidth allocation scheme for video multicast services.

We have presented various bandwidth allocation approaches for video services in IEEE 802.16e networks (i.e., single-hop WiMAX systems). The approaches in and allocate bandwidth by exploiting the common technology of scalable video coding (SVC) specified in the H.264/SVC standard. The H.264/SVC standard is extended from H.264/AVC, and can further split a video stream into a base layer for providing the basic video quality and multiple enhancement layers for providing better video quality layer by-layer.

4.4 EXPRIMENTAL RESULTS

PERFORMANCE IMPROVEMENT:

We investigate the performance improvement achieved by the hybrid network compared to the cellular-only network with varied number of mobile devices U. Fig. 6a shows with 95 percent confidence intervals that, for a PSNR requirement of 30 dB, the Current* scheduler can only support 10 mobile devices. POPT, MTS, and THS algorithms all achieve that quality with any investigated number of mobile devices. Note that these schedulers provide an advantage over Current*—mobile devices receive almost equally—good PSNR. That is, the longest range of 95 percent confidential interval achieved by POPT, MTS, and THS is merely 0.30 dB, while Current* suffers from a much larger range of up to 3.78 dB.

We observe that two algorithms, MTS and THS, achieve similar PSNR, at most 2 dB lower than POPT. Fig. 6b indicates that MTS is more efficient than POPT, but MTS’ running time still increases prohibitively with the increase of device density more device network, MTS takes more than half an hour to generate a schedule. In contrast, the THS algorithm always terminates in very short time under any number of devices. This shows that the THS algorithm achieves a good tradeoff between complexity and solution quality. Because MTS and THS achieve similar PSNR, but THS runs faster than MTS, we do not consider MTS in the remaining comparisons.

CHAPTER 4

5.0 SYSTEM STUDY:

5.1 FEASIBILITY STUDY:

The feasibility of the project is analyzed in this phase and business proposal is put forth with a very general plan for the project and some cost estimates. During system analysis the feasibility study of the proposed system is to be carried out. This is to ensure that the proposed system is not a burden to the company. For feasibility analysis, some understanding of the major requirements for the system is essential.

Three key considerations involved in the feasibility analysis are

ECONOMICAL FEASIBILITY
TECHNICAL FEASIBILITY
SOCIAL FEASIBILITY

5.1.1 ECONOMICAL FEASIBILITY:

This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.

5.1.2 TECHNICAL FEASIBILITY:

This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.

5.1.3 SOCIAL FEASIBILITY:

The aspect of study is to check the level of acceptance of the system by the user. This includes the process of training the user to use the system efficiently. The user must not feel threatened by the system, instead must accept it as a necessity. The level of acceptance by the users solely depends on the methods that are employed to educate the user about the system and to make him familiar with it. His level of confidence must be raised so that he is also able to make some constructive criticism, which is welcomed, as he is the final user of the system.

5.2 SYSTEM TESTING:

Testing is a process of checking whether the developed system is working according to the original objectives and requirements. It is a set of activities that can be planned in advance and conducted systematically. Testing is vital to the success of the system. System testing makes a logical assumption that if all the parts of the system are correct, the global will be successfully achieved. In adequate testing if not testing leads to errors that may not appear even many months. This creates two problems, the time lag between the cause and the appearance of the problem and the effect of the system errors on the files and records within the system. A small system error can conceivably explode into a much larger Problem. Effective testing early in the purpose translates directly into long term cost savings from a reduced number of errors. Another reason for system testing is its utility, as a user-oriented vehicle before implementation. The best programs are worthless if it produces the correct outputs.

5.2.1 UNIT TESTING:

A program represents the logical elements of a system. For a program to run satisfactorily, it must compile and test data correctly and tie in properly with other programs. Achieving an error free program is the responsibility of the programmer. Program testing checks for two types of errors: syntax and logical. Syntax error is a program statement that violates one or more rules of the language in which it is written. An improperly defined field dimension or omitted keywords are common syntax errors. These errors are shown through error message generated by the computer. For Logic errors the programmer must examine the output carefully.

UNIT TESTING:

Description	Expected result
Test for application window properties.	All the properties of the windows are to be properly aligned and displayed.
Test for mouse operations.	All the mouse operations like click, drag, etc. must perform the necessary operations without any exceptions.

5.1.3 FUNCTIONAL TESTING:

Functional testing of an application is used to prove the application delivers correct results, using enough inputs to give an adequate level of confidence that will work correctly for all sets of inputs. The functional testing will need to prove that the application works for each client type and that personalization function work correctly.When a program is tested, the actual output is compared with the expected output. When there is a discrepancy the sequence of instructions must be traced to determine the problem. The process is facilitated by breaking the program into self-contained portions, each of which can be checked at certain key points. The idea is to compare program values against desk-calculated values to isolate the problems.

FUNCTIONAL TESTING:

Description	Expected result
Test for all modules.	All peers should communicate in the group.
Test for various peer in a distributed network framework as it display all users available in the group.	The result after execution should give the accurate result.

5.1. 4 NON-FUNCTIONAL TESTING:

The Non Functional software testing encompasses a rich spectrum of testing strategies, describing the expected results for every test case. It uses symbolic analysis techniques. This testing used to check that an application will work in the operational environment. Non-functional testing includes:

Load testing
Performance testing
Usability testing
Reliability testing
Security testing

5.1.5 LOAD TESTING:

An important tool for implementing system tests is a Load generator. A Load generator is essential for testing quality requirements such as performance and stress. A load can be a real load, that is, the system can be put under test to real usage by having actual telephone users connected to it. They will generate test input data for system test.

Load Testing

Description	Expected result
It is necessary to ascertain that the application behaves correctly under loads when ‘Server busy’ response is received.	Should designate another active node as a Server.

5.1.5 PERFORMANCE TESTING:

Performance tests are utilized in order to determine the widely defined performance of the software system such as execution time associated with various parts of the code, response time and device utilization. The intent of this testing is to identify weak points of the software system and quantify its shortcomings.

PERFORMANCE TESTING:

Description	Expected result
This is required to assure that an application perforce adequately, having the capability to handle many peers, delivering its results in expected time and using an acceptable level of resource and it is an aspect of operational management.	Should handle large input values, and produce accurate result in a expected time.

5.1.6 RELIABILITY TESTING:

The software reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time and it is being ensured in this testing. Reliability can be expressed as the ability of the software to reveal defects under testing conditions, according to the specified requirements. It the portability that a software system will operate without failure under given conditions for a given time interval and it focuses on the behavior of the software element. It forms a part of the software quality control team.

RELIABILITY TESTING:

Description	Expected result
This is to check that the server is rugged and reliable and can handle the failure of any of the components involved in provide the application.	In case of failure of the server an alternate server should take over the job.

5.1.7 SECURITY TESTING:

Security testing evaluates system characteristics that relate to the availability, integrity and confidentiality of the system data and services. Users/Clients should be encouraged to make sure their security needs are very clearly known at requirements time, so that the security issues can be addressed by the designers and testers.

SECURITY TESTING:

Description	Expected result
Checking that the user identification is authenticated.	In case failure it should not be connected in the framework.
Check whether group keys in a tree are shared by all peers.	The peers should know group key in the same group.

5.1.7 WHITE BOX TESTING:

White box testing, sometimes called glass-box testing is a test case design method that uses the control structure of the procedural design to derive test cases. Using white box testing method, the software engineer can derive test cases. The White box testing focuses on the inner structure of the software structure to be tested.

5.1.8 WHITE BOX TESTING:

Description	Expected result
Exercise all logical decisions on their true and false sides.	All the logical decisions must be valid.
Execute all loops at their boundaries and within their operational bounds.	All the loops must be finite.
Exercise internal data structures to ensure their validity.	All the data structures must be valid.

5.1.9 BLACK BOX TESTING:

Black box testing, also called behavioral testing, focuses on the functional requirements of the software. That is, black testing enables the software engineer to derive sets of input conditions that will fully exercise all functional requirements for a program. Black box testing is not alternative to white box techniques. Rather it is a complementary approach that is likely to uncover a different class of errors than white box methods. Black box testing attempts to find errors which focuses on inputs, outputs, and principle function of a software module. The starting point of the black box testing is either a specification or code. The contents of the box are hidden and the stimulated software should produce the desired results.

5.1.10 BLACK BOX TESTING:

Description	Expected result
To check for incorrect or missing functions.	All the functions must be valid.
To check for interface errors.	The entire interface must function normally.
To check for errors in a data structures or external data base access.	The database updation and retrieval must be done.
To check for initialization and termination errors.	All the functions and data structures must be initialized properly and terminated normally.

All the above system testing strategies are carried out in as the development, documentation and institutionalization of the proposed goals and related policies is essential.

CHAPTER 7

7.0 SOFTWARE DESCRIPTION:

7.1 JAVA TECHNOLOGY:

Java technology is both a programming language and a platform.

The Java Programming Language

The Java programming language is a high-level language that can be characterized by all of the following buzzwords:

Simple
- Architecture neutral
- Object oriented
- Portable
- Distributed
- High performance
- Interpreted
- Multithreaded
- Robust
- Dynamic
- Secure

With most programming languages, you either compile or interpret a program so that you can run it on your computer. The Java programming language is unusual in that a program is both compiled and interpreted. With the compiler, first you translate a program into an intermediate language called Java byte codes —the platform-independent codes interpreted by the interpreter on the Java platform. The interpreter parses and runs each Java byte code instruction on the computer. Compilation happens just once; interpretation occurs each time the program is executed. The following figure illustrates how this works.

You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether it’s a development tool or a Web browser that can run applets, is an implementation of the Java VM. Java byte codes help make “write once, run anywhere” possible. You can compile your program into byte codes on any platform that has a Java compiler. The byte codes can then be run on any implementation of the Java VM. That means that as long as a computer has a Java VM, the same program written in the Java programming language can run on Windows 2000, a Solaris workstation, or on an iMac.

7.2 THE JAVA PLATFORM:

A platform is the hardware or software environment in which a program runs. We’ve already mentioned some of the most popular platforms like Windows 2000, Linux, Solaris, and MacOS. Most platforms can be described as a combination of the operating system and hardware. The Java platform differs from most other platforms in that it’s a software-only platform that runs on top of other hardware-based platforms.

The Java platform has two components:

The Java Virtual Machine (Java VM)
The Java Application Programming Interface (Java API)

You’ve already been introduced to the Java VM. It’s the base for the Java platform and is ported onto various hardware-based platforms.

The Java API is a large collection of ready-made software components that provide many useful capabilities, such as graphical user interface (GUI) widgets. The Java API is grouped into libraries of related classes and interfaces; these libraries are known as packages. The next section, What Can Java Technology Do? Highlights what functionality some of the packages in the Java API provide.

The following figure depicts a program that’s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.

Native code is code that after you compile it, the compiled code runs on a specific hardware platform. As a platform-independent environment, the Java platform can be a bit slower than native code. However, smart compilers, well-tuned interpreters, and just-in-time byte code compilers can bring performance close to that of native code without threatening portability.

7.3 WHAT CAN JAVA TECHNOLOGY DO?

The most common types of programs written in the Java programming language are applets and applications. If you’ve surfed the Web, you’re probably already familiar with applets. An applet is a program that adheres to certain conventions that allow it to run within a Java-enabled browser.

However, the Java programming language is not just for writing cute, entertaining applets for the Web. The general-purpose, high-level Java programming language is also a powerful software platform. Using the generous API, you can write many types of programs.

An application is a standalone program that runs directly on the Java platform. A special kind of application known as a server serves and supports clients on a network. Examples of servers are Web servers, proxy servers, mail servers, and print servers. Another specialized program is a servlet.

A servlet can almost be thought of as an applet that runs on the server side. Java Servlets are a popular choice for building interactive web applications, replacing the use of CGI scripts. Servlets are similar to applets in that they are runtime extensions of applications. Instead of working in browsers, though, servlets run within Java Web servers, configuring or tailoring the server.

How does the API support all these kinds of programs? It does so with packages of software components that provides a wide range of functionality. Every full implementation of the Java platform gives you the following features:

The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
Applets: The set of conventions used by applets.
Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
Software components: Known as JavaBeans^TM, can plug into existing component architectures.
Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
Java Database Connectivity (JDBC^TM): Provides uniform access to a wide range of relational databases.

The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.

7.4 HOW WILL JAVA TECHNOLOGY CHANGE MY LIFE?

We can’t promise you fame, fortune, or even a job if you learn the Java programming language. Still, it is likely to make your programs better and requires less effort than other languages. We believe that Java technology will help you do the following:

Get started quickly: Although the Java programming language is a powerful object-oriented language, it’s easy to learn, especially for programmers already familiar with C or C++.
Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people’s tested code and introduce fewer bugs.
Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why? You write fewer lines of code and it is a simpler programming language than C++.
Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure Java^TMProduct Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded “on the fly,” without recompiling the entire program.

7.5 ODBC:

Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.

Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.

The ODBC system files are not installed on your system by Windows 95. Rather, they are installed when you setup a separate database application, such as SQL Server Client or Visual Basic 4.0. When the ODBC icon is installed in Control Panel, it uses a file called ODBCINST.DLL. It is also possible to administer your ODBC data sources through a stand-alone program called ODBCADM.EXE. There is a 16-bit and a 32-bit version of this program and each maintains a separate list of ODBC data sources.

From a programming perspective, the beauty of ODBC is that the application can be written to use the same set of function calls to interface with any data source, regardless of the database vendor. The source code of the application doesn’t change whether it talks to Oracle or SQL Server. We only mention these two as an example. There are ODBC drivers available for several dozen popular database systems. Even Excel spreadsheets and plain text files can be turned into data sources. The operating system uses the Registry information written by ODBC Administrator to determine which low-level ODBC drivers are needed to talk to the data source (such as the interface to Oracle or SQL Server). The loading of the ODBC drivers is transparent to the ODBC application program. In a client/server environment, the ODBC API even handles many of the network issues for the application programmer.

The advantages of this scheme are so numerous that you are probably thinking there must be some catch. The only disadvantage of ODBC is that it isn’t as efficient as talking directly to the native database interface. ODBC has had many detractors make the charge that it is too slow. Microsoft has always claimed that the critical factor in performance is the quality of the driver software that is used. In our humble opinion, this is true. The availability of good ODBC drivers has improved a great deal recently. And anyway, the criticism about performance is somewhat analogous to those who said that compilers would never match the speed of pure assembly language. Maybe not, but the compiler (or ODBC) gives you the opportunity to write cleaner programs, which means you finish sooner. Meanwhile, computers get faster every year.

7.6 JDBC:

In an effort to set an independent database standard API for Java; Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of “plug-in” database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.

To gain a wider acceptance of JDBC, Sun based JDBC’s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.

JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

The remainder of this section will cover enough information about JDBC for you to know what it is about and how to use it effectively. This is by no means a complete overview of JDBC. That would fill an entire book.

7.7 JDBC Goals:

Few software packages are designed without goals in mind. JDBC is one that, because of its many goals, drove the development of the API. These goals, in conjunction with early reviewer feedback, have finalized the JDBC class library into a solid framework for building database applications in Java.

The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:

SQL Level API

The designers felt that their main goal was to define a SQL interface for Java. Although not the lowest database interface level possible, it is at a low enough level for higher-level tools and APIs to be created. Conversely, it is at a high enough level for application programmers to use it confidently. Attaining this goal allows for future tool vendors to “generate” JDBC code and to hide many of JDBC’s complexities from the end user.

SQL Conformance

SQL syntax varies as you move from database vendor to database vendor. In an effort to support a wide variety of vendors, JDBC will allow any query statement to be passed through it to the underlying database driver. This allows the connectivity module to handle non-standard functionality in a manner that is suitable for its users.

JDBC must be implemental on top of common database interfaces

The JDBC SQL API must “sit” on top of other common SQL level APIs. This goal allows JDBC to use existing ODBC level drivers by the use of a software interface. This interface would translate JDBC calls to ODBC and vice versa.

Provide a Java interface that is consistent with the rest of the Java system

Because of Java’s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.

Keep it simple

This goal probably appears in all software design goal listings. JDBC is no exception. Sun felt that the design of JDBC should be very simple, allowing for only one method of completing a task per mechanism. Allowing duplicate functionality only serves to confuse the users of the API.

Use strong, static typing wherever possible

Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.

Keep the common cases simple

Because more often than not, the usual SQL calls used by the programmer are simple SELECT’s, INSERT’s, DELETE’s and UPDATE’s, these queries should be simple to perform with JDBC. However, more complex SQL statements should also be possible.

Finally we decided to precede the implementation using Java Networking.

And for dynamically updating the cache table we go for MS Access database.

Java ha two things: a programming language and a platform.

Java is a high-level programming language that is all of the following

Simple Architecture-neutral

Object-oriented Portable

Distributed High-performance

Interpreted Multithreaded

Robust Dynamic Secure

Java is also unusual in that each Java program is both compiled and interpreted. With a compile you translate a Java program into an intermediate language called Java byte codes the platform-independent code instruction is passed and run on the computer.

Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.

7.7 NETWORKING TCP/IP STACK:

The TCP/IP stack is shorter than the OSI one:

TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.

IP datagram’s:

The IP layer provides a connectionless and unreliable delivery system. It considers each datagram independently of the others. Any association between datagram must be supplied by the higher layers. The IP layer supplies a checksum that includes its own header. The header includes the source and destination addresses. The IP layer handles routing through an Internet. It is also responsible for breaking up large datagram into smaller ones for transmission and reassembling them at the other end.

UDP:

UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model – see later.

TCP:

TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.

Internet addresses

In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address.

Network address:

Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.

Subnet address:

Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.

Host address:

8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.

Total address:

The 32 bit address is usually written as 4 integers separated by dots.

Port addresses

A service exists on a host, and is identified by its port. This is a 16 bit number. To send a message to a server, you send it to the port for that service of the host that it is running on. This is not location transparency! Certain of these ports are “well known”.

Sockets:

A socket is a data structure maintained by the system to handle network connections. A socket is created using the call socket. It returns an integer that is like a file descriptor. In fact, under Windows, this handle can be used with Read File and Write File functions.

#include <sys/types.h>

#include <sys/socket.h>

int socket(int family, int type, int protocol);

Here “family” will be AF_INET for IP communications, protocol will be zero, and type will depend on whether TCP or UDP is used. Two processes wishing to communicate over a network create a socket each. These are similar to two ends of a pipe – but the actual pipe does not yet exist.

7.8 JFREE CHART:

JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart’s extensive feature set includes:

A consistent and well-documented API, supporting a wide range of chart types;

A flexible design that is easy to extend, and targets both server-side and client-side applications;

Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);

JFreeChart is “open source” or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.

7.8.1. Map Visualizations:

Charts showing values that relate to geographical areas. Some examples include: (a) population density in each state of the United States, (b) income per capita for each country in Europe, (c) life expectancy in each country of the world. The tasks in this project include: Sourcing freely redistributable vector outlines for the countries of the world, states/provinces in particular countries (USA in particular, but also other areas);

Creating an appropriate dataset interface (plus default implementation), a rendered, and integrating this with the existing XYPlot class in JFreeChart; Testing, documenting, testing some more, documenting some more.

7.8.2. Time Series Chart Interactivity

Implement a new (to JFreeChart) feature for interactive time series charts — to display a separate control that shows a small version of ALL the time series data, with a sliding “view” rectangle that allows you to select the subset of the time series data to display in the main chart.

7.8.3. Dashboards

There is currently a lot of interest in dashboard displays. Create a flexible dashboard mechanism that supports a subset of JFreeChart chart types (dials, pies, thermometers, bars, and lines/time series) that can be delivered easily via both Java Web Start and an applet.

7.8.4. Property Editors

The property editor mechanism in JFreeChart only handles a small subset of the properties that can be set for charts. Extend (or reimplement) this mechanism to provide greater end-user control over the appearance of the charts.

CHAPTER 7

APPENDIX

7.1 SAMPLE SOURCE CODE

7.2 SAMPLE OUTPUT

CHAPTER 8

8.1 CONCLUSION

We proposed algorithms: 1) an MILP-based algorithm called POPT a greedy algorithm, THS. Via packet-level simulations, we found that neither POPT nor MTS scale to large hybrid networks. This is because they both employ numerical methods to solve optimization problems. Therefore, we recommend the THS algorithm, which terminates in real time even when there are 70+ mobile devices in the hybrid network.

The experimental results from the actual testbed confirm the observations we made in Qualnet simulations: the THS algorithm clearly outperforms the Current* algorithm. Furthermore, the THS algorithm may outperform POPT in real systems, which can be attributed to the long running time of the POPT algorithm. This demonstrates that the THS algorithm is practical and efficient.

The simulation results indicate that the THS algorithm not only runs fast, but also achieves overall video quality close to the optimum: at most 2 dB difference is observed, compared to the POPT algorithm. In contrast, optimum schedules over the cellular network achieve much lower video quality compared to POPT: more than 15 dB difference is observed. We also validated the practicality and efficiency of the THS algorithm using a real testbed in a live cellular network. The experimental results confirm that the THS algorithm result in high video quality. Moreover, the THS algorithm could outperform the POPT algorithm in real systems. This is because although POPT could generate optimal schedules, its high running time may lead to many late segments, which in turn render inferior video quality.